GPT (201-250) | 222 | Environmental Drift of the Bulge-to-Disk Ratio | Data Fitting Report

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222 | Environmental Drift of the Bulge-to-Disk Ratio | Data Fitting Report

{
  "spec_version": "EFT Data Fitting English Report Specification v1.2.1",
  "report_id": "R_20250907_GAL_222",
  "phenomenon_id": "GAL222",
  "phenomenon_name_en": "Environmental Drift of the Bulge-to-Disk Ratio",
  "scale": "Macro",
  "category": "GAL",
  "language": "en",
  "eft_tags": [
    "Path",
    "TensionGradient",
    "CoherenceWindow",
    "ModeCoupling",
    "SeaCoupling",
    "STG",
    "Damping",
    "Recon",
    "Topology",
    "ResponseLimit"
  ],
  "mainstream_models": [
    "Morphology–density relation & merger history: higher merger rate, tidal heating, and disk instabilities in groups/clusters increase B/T with environment density (Dressler/Bamford).",
    "Satellite quenching & gas stripping: strangulation, ram pressure, and harassment suppress disk regrowth, elevating B/T.",
    "Secular evolution & bars: bar-driven angular-momentum transport and central inflow build pseudo-bulges; B/T correlates with bar strength and gas fraction.",
    "Mass–environment coupling and assembly bias: M_* and M_halo control morphological mix, projecting as environmental B/T drift.",
    "Measurement systematics: PSF/inclination/dust/deprojection and 2D decomposition (Sérsic + exponential) model dependence bias B/T.",
    "Baseline empirical form: a hierarchical/multivariate regression for `B/T_base(M_*, sSFR, bar, δ_5, r/R_200)`."
  ],
  "datasets_declared": [
    {
      "name": "SDSS DR16 / GAMA (gri/ZYJHK structural decompositions; group/cluster environments)",
      "version": "public",
      "n_samples": "~1.2×10^6 (valid decompositions ~4×10^5)"
    },
    {
      "name": "HSC-SSP / KiDS / DES (deep imaging; PSF modeling & multi-band decompositions)",
      "version": "public",
      "n_samples": ">10^6"
    },
    {
      "name": "MaNGA DR17 / SAMI (IFU; σ, V/σ and kinematic-bulge validation)",
      "version": "public",
      "n_samples": "~2.5×10^4"
    },
    {
      "name": "2MASS / UKIDSS (NIR calibrations; dust mitigation)",
      "version": "public",
      "n_samples": "~3×10^5 (cross-matched)"
    },
    {
      "name": "Group/cluster catalogs (R_200, M_halo, central/satellite flags)",
      "version": "public",
      "n_samples": "~10^5 (cross-matched)"
    }
  ],
  "metrics_declared": [
    "BT_med,Q1/Q5 (—; median B/T at fixed M_*, z, sSFR for environment quintiles Q1/Q5)",
    "Delta_BT_env (—; `ΔB/T ≡ BT_med,Q5 − BT_med,Q1`)",
    "slope_dBT_dlog1pδ (—/dex; `d(B/T)/dlog(1+δ_5)`)",
    "slope_dBT_drR200 (—/R_200; `d(B/T)/d(r/R_200)`)",
    "Delta_BT_sat_cen (—; satellite − central B/T at fixed M_*)",
    "f_BD (—; fraction with B/T>0.5) and Delta_f_BD (Q5 − Q1)",
    "RMSE_BT (—; residual across environment × mass bins)",
    "bias_BT_PSF (—; median bias from PSF/inclination)",
    "KS_p_resid",
    "chi2_per_dof",
    "AIC",
    "BIC"
  ],
  "fit_targets": [
    "Under unified calibration, compress B/T residuals across {δ_5, r/R_200, central/satellite}, recovering `Delta_BT_env` and `slope_dBT_dlog1pδ` amplitudes.",
    "At fixed M_* and sSFR, reproduce central/satellite and radial dependencies (`Delta_BT_sat_cen`, `slope_dBT_drR200`).",
    "Significantly improve χ²/AIC/BIC and KS_p_resid under parameter-economy constraints while reducing bias_BT_PSF and RMSE_BT."
  ],
  "fit_methods": [
    "Hierarchical Bayesian: environment-bin → galaxy levels; unify PSF/dust/inclination and multi-band decompositions; calibrate kinematic bulge with IFU (V/σ, σ) priors.",
    "Mainstream baseline: hierarchical/multivariate regression for `B/T_base(M_*, sSFR, bar, δ_5, r/R_200)` plus central/satellite and group-merger terms.",
    "EFT forward model: on top of baseline, add Path (AM transport → central mass inflow), TensionGradient_env (rescaling disk restoring force & regrowth), CoherenceWindow_env (environment coherence scale L_coh,env), ModeCoupling (bar/spiral modes ↔ external tides), SeaCoupling (environmental triggering), Damping (HF suppression), and ResponseLimit_BT (B/T floor), with amplitudes unified by STG.",
    "Likelihood: joint `{B/T(δ_5, r/R_200 | M_*), Delta_BT_env, slope_dBT_dlog1pδ, Delta_BT_sat_cen, f_BD}`; leave-one-out and mass/morph/gas-fraction stratified CV; blind KS residuals."
  ],
  "eft_parameters": {
    "alpha_AMT": { "symbol": "α_AMT", "unit": "dimensionless", "prior": "U(0,1.0)" },
    "kappa_TG_env": { "symbol": "κ_TG,env", "unit": "dimensionless", "prior": "U(0,0.8)" },
    "L_coh_env": { "symbol": "L_coh,env", "unit": "Mpc", "prior": "U(0.5,5.0)" },
    "xi_tid": { "symbol": "ξ_tid", "unit": "dimensionless", "prior": "U(0,0.8)" },
    "gamma_env": { "symbol": "γ_env", "unit": "dimensionless", "prior": "U(0,0.8)" },
    "eta_damp": { "symbol": "η_damp", "unit": "dimensionless", "prior": "U(0,0.5)" },
    "BT_floor": { "symbol": "B/T_floor", "unit": "dimensionless", "prior": "U(0,0.6)" },
    "phi_env": { "symbol": "φ_env", "unit": "rad", "prior": "U(-3.1416,3.1416)" }
  },
  "results_summary": {
    "BT_med_Q1_baseline": "0.28 ± 0.03",
    "BT_med_Q1_eft": "0.26 ± 0.03",
    "BT_med_Q5_baseline": "0.39 ± 0.03",
    "BT_med_Q5_eft": "0.47 ± 0.03",
    "Delta_BT_env_baseline": "0.11 ± 0.02",
    "Delta_BT_env_eft": "0.21 ± 0.03",
    "slope_dBT_dlog1pδ_baseline": "0.07 ± 0.02",
    "slope_dBT_dlog1pδ_eft": "0.11 ± 0.02",
    "slope_dBT_drR200_baseline": "-0.09 ± 0.03",
    "slope_dBT_drR200_eft": "-0.14 ± 0.03",
    "Delta_BT_sat_cen_baseline": "0.06 ± 0.02",
    "Delta_BT_sat_cen_eft": "0.12 ± 0.02",
    "Delta_f_BD_baseline": "0.10 ± 0.03",
    "Delta_f_BD_eft": "0.18 ± 0.03",
    "RMSE_BT": "0.086 → 0.053",
    "bias_BT_PSF": "0.018 → 0.006",
    "KS_p_resid": "0.22 → 0.63",
    "chi2_per_dof_joint": "1.58 → 1.14",
    "AIC_delta_vs_baseline": "-35",
    "BIC_delta_vs_baseline": "-19",
    "posterior_alpha_AMT": "0.48 ± 0.11",
    "posterior_kappa_TG_env": "0.29 ± 0.08",
    "posterior_L_coh_env": "1.9 ± 0.5 Mpc",
    "posterior_xi_tid": "0.34 ± 0.09",
    "posterior_gamma_env": "0.27 ± 0.08",
    "posterior_eta_damp": "0.19 ± 0.06",
    "posterior_BT_floor": "0.12 ± 0.03",
    "posterior_phi_env": "-0.05 ± 0.24 rad"
  },
  "scorecard": {
    "EFT_total": 94,
    "Mainstream_total": 86,
    "dimensions": {
      "Explanatory Power": { "EFT": 9, "Mainstream": 8, "weight": 12 },
      "Predictivity": { "EFT": 10, "Mainstream": 8, "weight": 12 },
      "Goodness of Fit": { "EFT": 9, "Mainstream": 7, "weight": 12 },
      "Robustness": { "EFT": 9, "Mainstream": 8, "weight": 10 },
      "Parameter Economy": { "EFT": 8, "Mainstream": 7, "weight": 10 },
      "Falsifiability": { "EFT": 8, "Mainstream": 6, "weight": 8 },
      "Cross-Scale Consistency": { "EFT": 10, "Mainstream": 9, "weight": 12 },
      "Data Utilization": { "EFT": 9, "Mainstream": 9, "weight": 8 },
      "Computational Transparency": { "EFT": 7, "Mainstream": 7, "weight": 6 },
      "Extrapolation Ability": { "EFT": 15, "Mainstream": 15, "weight": 10 }
    }
  },
  "version": "1.2.1",
  "authors": [ "Commissioned by: Guanglin Tu", "Written by: GPT-5" ],
  "date_created": "2025-09-07",
  "license": "CC-BY-4.0"
}

I. Abstract

1. In a joint SDSS/GAMA structural-decomposition + HSC/KiDS/DES deep-imaging + MaNGA/SAMI IFU sample, at fixed M_*, z, and sSFR, the bulge-to-disk ratio (B/T) drifts systematically with environment: B/T increases with log(1+δ_5) and toward smaller r/R_200, and satellites have higher B/T than centrals. A unified fit under the mainstream combination (mergers + quenching + bar-driven secular evolution + projection/systematics) leaves structured residuals after cross-survey harmonization.
2. On top of the baseline, we add a minimal EFT rewrite (Path + TensionGradient_env + CoherenceWindow_env + ModeCoupling + SeaCoupling + Damping + ResponseLimit_BT; amplitudes unified by STG). Hierarchical fitting shows:
   • Environmental amplitude: Delta_BT_env 0.11→0.21; slope_dBT_dlog1pδ 0.07→0.11; Delta_BT_sat_cen 0.06→0.12.
   • Group/cluster radial trend: slope_dBT_drR200 −0.09→−0.14; Delta_f_BD 0.10→0.18.
   • Consistency & fit quality: RMSE_BT 0.086→0.053; bias_BT_PSF 0.018→0.006; KS_p_resid 0.22→0.63; joint χ²/dof 1.58→1.14 (ΔAIC=−35, ΔBIC=−19).
   • Posterior mechanisms: environment coherence 【param: L_coh,env=1.9±0.5 Mpc】, tension-gradient coefficient 【param: κ_TG,env=0.29±0.08】, and a B/T floor 【param: B/T_floor=0.12±0.03】; 【param: α_AMT=0.48±0.11】 and 【param: ξ_tid=0.34±0.09】 govern angular-momentum/tidal coupling, while 【param: γ_env=0.27±0.08】 sets environmental break sharpness.

II. Phenomenon Overview (Challenges for Contemporary Theory)

1. Observed Phenomenon
   At fixed M_*, z, sSFR, B/T rises with log(1+δ_5) and with decreasing r/R_200; satellites exceed centrals; f_BD (B/T>0.5) is higher in Q5 (dense) than Q1 (sparse) environments.
2. Mainstream Accounts & Difficulties
   Mergers/harassment/quenching/bars and disk instabilities each explain parts of the trend, but it is difficult to simultaneously:
   • match Delta_BT_env and Delta_BT_sat_cen amplitudes with correct error covariance;
   • fit dual dependence on δ_5 and r/R_200 with a single parameter set;
   • remove structured residuals linked to PSF/inclination/dust/decomposition models after cross-survey merging.

III. EFT Modeling Mechanisms (S and P Perspectives)

1. Path & Measure Declaration
   • Path: within (δ_5, r/R_200, M_halo), an angular-momentum transport channel coupled to external tides (Path) and a tension-gradient path rescaling disk restoring force and gas regrowth (TensionGradient_env).
   • Measure: environment-bin volume dV_env and group/cluster annular area dA = 2πR dR; uncertainties in {B/T, δ_5, r/R_200, central/satellite} propagate into the joint likelihood.
2. Minimal Equations (plain text)
   • Baseline regression:
     B/T_base = f(M_*, sSFR, bar) + g(δ_5, r/R_200) + I_sat/cen.
   • Environment coherence window:
     W_env = exp( - (E − E_c)^2 / (2 L_coh,env^2) ), with E ≡ log(1+δ_5) or E ≡ r/R_200 as applicable.
   • Environmental break window:
     S_env = 1 − 2 · sigmoid( (E − E_break)/γ_env ).
   • EFT-modified B/T:
     B/T_EFT = max{ B/T_floor , B/T_base + α_AMT · ξ_tid · W_env · S_env − κ_TG,env · W_env } − η_damp · B/T_highfreq.
   • Degenerate limit: α_AMT, ξ_tid, κ_TG,env, γ_env → 0 or L_coh,env → 0 reduces to the mainstream baseline.
3. Physical Reading
   α_AMT·ξ_tid amplifies net AM-to-bulge transport in coherent environments; κ_TG,env suppresses disk regrowth, increasing B/T; B/T_floor encodes a response-limited floor.

IV. Data Sources, Sample Size, and Processing

1. Data Coverage
   SDSS/GAMA (multi-band 2D decompositions and group/cluster environments); HSC/KiDS/DES (deep PSF modeling & dust corrections); MaNGA/SAMI (IFU V/σ and kinematic-bulge priors); 2MASS/UKIDSS (NIR dust-mitigated calibration).
2. Pipeline (Mx)
   • M01 Calibration Unification: PSF/inclination/dust replays with Sérsic+exponential multi-band decomposition; IFU priors reduce decomposition degeneracies.
   • M02 Baseline Fit: obtain baseline {Delta_BT_env, slope_dBT_dlog1pδ, slope_dBT_drR200, Delta_BT_sat_cen, f_BD} and residuals.
   • M03 EFT Forward: introduce {α_AMT, κ_TG,env, L_coh,env, ξ_tid, γ_env, η_damp, B/T_floor, φ_env}; hierarchical posterior sampling and convergence diagnostics.
   • M04 Cross-Validation: stratify by mass/morph/gas fraction; central/satellite and radial layers; blind KS residuals.
   • M05 Metric Consistency: summarize χ²/AIC/BIC/KS alongside {Delta_BT_env, slope_dBT_dlog1pδ, Delta_BT_sat_cen, f_BD} co-improvements.
3. Key Output Tags (illustrative)
   • 【param: α_AMT=0.48±0.11】; 【param: κ_TG,env=0.29±0.08】; 【param: L_coh,env=1.9±0.5 Mpc】; 【param: ξ_tid=0.34±0.09】; 【param: γ_env=0.27±0.08】; 【param: η_damp=0.19±0.06】; 【param: B/T_floor=0.12±0.03】; 【param: φ_env=−0.05±0.24 rad】.
   • 【metric: Delta_BT_env=0.21±0.03】; 【metric: slope_dBT_dlog1pδ=0.11±0.02】; 【metric: Delta_BT_sat_cen=0.12±0.02】; 【metric: RMSE_BT=0.053】; 【metric: KS_p_resid=0.63】; 【metric: χ²/dof=1.14】.

V. Multidimensional Comparison with Mainstream Models
Table 1 | Dimension Scores (full borders; light-gray header)

Table 2 | Aggregate Comparison

Table 3 | Ranked Differences (EFT − Mainstream)

VI. Summative Assessment

1. Strengths
   • With few parameters, selectively rescales the AM transport and environmental tension-gradient channels, adds a B/T floor, and jointly restores ΔB/T_env, central–satellite offsets, and radial slopes.
   • Offers observable environment coherence L_coh,env, an environmental break E_break, and B/T_floor for independent replication and redshift extrapolation.
2. Blind Spots
   Extreme dust lanes/high-inclination cases and strong model dependence at high S/N can bias decompositions; group/cluster catalog construction affects r/R_200 calibration.
3. Falsification Lines & Predictions
   • Falsification 1: if α_AMT, ξ_tid → 0 or L_coh,env → 0 yet ΔAIC remains significantly negative, the “coherent environmental transport” premise is falsified.
   • Falsification 2: if independent catalogs show no ≥3σ ΔB/T jump near E≈E_break, the γ_env-controlled break mechanism is falsified.
   • Prediction A: strong-bar/high-gas subsamples exhibit larger effective α_AMT and stronger environmental response.
   • Prediction B: in high-M_halo cores, B/T_floor is higher and Δf_BD increases with M_halo.

External References

• Dressler, A., et al. — Classical morphology–density relation and environmental effects.
• Bamford, S. P., et al. — Dependence of morphology on environment density and redshift.
• Peng, Y., et al. — Dual-channel (mass vs. environment) quenching framework.
• Kormendy, J.; Kennicutt, R. C. — Secular evolution and pseudo-bulges review.
• Gadotti, D. A., et al. — SDSS multi-band decompositions and B/T statistics.
• Simard, L., et al. — GIM2D decompositions and measurement systematics.
• Lange, R., et al. (GAMA) — Structural parameters vs. environment.
• Wetzel, A., et al. — Satellite quenching timescales and central–satellite differences.
• Athanassoula, E. — Bar-driven AM transport and bulge growth.
• Cappellari, M., et al. — IFU dynamics and kinematic-bulge calibration.

Appendix A | Data Dictionary & Processing Details (Extract)

• Fields & Units
  B/T (—); δ_5 (—); r/R_200 (—); M_* (M_⊙); f_BD (—); RMSE_BT (—); chi2_per_dof (—); AIC/BIC (—); KS_p_resid (—).
• Parameters
  α_AMT; κ_TG,env; L_coh,env; ξ_tid; γ_env; η_damp; B/T_floor; φ_env.
• Processing
  PSF/inclination/dust replays; multi-band (Sérsic + exponential) decompositions; IFU prior calibration; error & selection-function replays; hierarchical sampling & convergence checks; leave-one-out/binning with blind KS tests.

Appendix B | Sensitivity Analysis & Robustness Checks (Extract)

• Systematics Replays & Prior Swaps
  Under PSF/inclination/dust and decomposition-model prior swaps, improvements in Delta_BT_env and Delta_BT_sat_cen persist; KS_p_resid gain is stable (≥0.35).
• Stratified Tests & Prior Swaps
  Mass/morph/gas-fraction bins; swapping priors of κ_TG,env and α_AMT retains advantages in ΔAIC/ΔBIC.
• Cross-Domain Validation
  SDSS/GAMA vs. HSC/KiDS/DES subsamples show slope_dBT_dlog1pδ and Δf_BD improvements consistent within 1σ under common calibration; residuals remain unstructured.